Wireless service providers are observing an exponential growth in mobile communications due to both an increase in consumer demand and commercial requirements. Moreover, to ensure customer satisfaction, wireless service providers aim to deliver a high quality service to facilitate reliable and efficient mobile communications at all locations. However, wireless data usage has become difficult to predict and localize, and it is often difficult to tune the wireless network to suit this usage. Oftentimes, traffic demand at a specific location can change over time; for example, demand within a rural area, without network coverage, can suddenly increase due to a natural disaster or network capacity within a densely populated urban area can suddenly become inefficient due to a large event.
Conventional systems utilize received signal strength indicator (RSSI) and/or angle of arrival (AoA) measurement data received from user equipments (UEs), to determine whether radio access network (RAN) capacity is sufficient. However, this approach is expensive, time consuming and negatively affects battery lives of the UEs. In addition, this approach provides static provisioning based on UE measurement data and network devices cannot adapt to sudden changes in traffic demand, for example, due to an emergency event, special event, and/or external event.